Genome-wide Investigation of Alcohol Response: A Meta-Analytic Review and Polygenic Associations with AUD

酒精反应的全基因组调查：荟萃分析综述以及与 AUD 的多基因关联

• 批准号: 9258286
• 负责人: Joseph D. Deak
• 金额: $ 4.03万
• 依托单位: UNIVERSITY OF MISSOURI-COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9258286
• 关键词: Address; Alcohol consumption; Alcohol dependence; Alcohols; Architecture; Biological; Clinical; Collaborations; Complex; Data; Data Analyses; Data Analytics; Data Set; Development; Diagnosis; Diagnostic; Disease; Ensure; Etiology; Family; Family Study; Feedback; Foundations; Future; Genetic; Genetic Risk; Genetic Variation; Genetic study; Genome; Genotype; Goals; Health; Heterogeneity; Individual; Intervention; Investigation; Knowledge; Letters; Measures; Meta-Analysis; Methods; Modeling; Molecular Genetics; Motor; Nature; Outcome; Phenotype; Physiological; Positioning Attribute; Predisposition; Prevalence; Prevention; Prevention program; Preventive Intervention; Procedures; Process; Quality Control; Reporting; Research; Research Design; Research Domain Criteria; Risk; Risk Factors; Role; Sample Size; Sampling; Substance Use Disorder; Susceptibility Gene; System; Testing; Training; Twin Multiple Birth; Twin Studies; United States; Variant; abstracting; alcohol effect; alcohol expectancy; alcohol response; alcohol use disorder; base; career; case control; cost; database of Genotypes and Phenotypes; design; disorder risk; dosage; drinking; endophenotype; experience; genetic information; genetic variant; genome wide association study; genome-wide; high risk; improved; interest; meetings; mortality; programs; psychologic; response; socioeconomics; tenure track; tool; trait

(7) Project Summary/Abstract Specific Aims The current proposal first aims to extend previous genetic studies of level of response (LR) to alcohol by conducting the largest genome-wide association study (GWAS) of LR to date through the meta-analysis of multiple samples with extant SRE (Self-Rating of the Effects of Alcohol) and GWAS data. A second aim is to use summary data from the described GWAS of LR to create polygenic risk scores in an independent sample in order to determine whether, and to what extent, the genetic influences underlying LR to alcohol serve as a risk factor for AUD. Method Towards the abovementioned aims, datasets will be processed according to standard quality control (QC) procedures (e.g., Anderson et al., 2010) allowing for genotype imputation to a common reference panel and GWA analysis of each dataset using methods appropriate for the individual study designs. For all identified samples (see attached contribution letters) Dr. Marc Schuckit (consultant) will provide critical support in decisions regarding the use of the SRE phenotype. All data-analytic procedures will be conducted in coordination with Dr. Ian Gizer (sponsor), Dr. Arpana Agrawal (consultant), and the respective dataset contributors to ensure that all data are analyzed according to mutually-agreed upon procedures. Following individual study-level GWA analyses, standardized GWAS meta-analysis QC procedures will be carried out (Winkler et al., 2014) and a meta-analysis combining results from all samples will be conducted utilizing a fixed-effects model in METAL (Willer et al., 2010). Lastly, results from the SRE meta-analysis will be utilized to compute polygenic risk scores (PRS) in an independent target sample to examine the predictive ability of the LR to alcohol PRS for AUD outcomes. The Australian Twin Families (OZ-ALC GWAS) sample accessed from the database of Genotypes and Phenotypes (dbGaP) will be used to accomplish this second aim. Long-Term Objectives The over-arching goal of the current proposal is to utilize GWA meta-analytic procedures and polygenic modeling approaches to synthesize quantitative data across multiple GWA datasets in order to advance our understanding of the genetic architecture of AUD etiology, as well as a well-established biological risk mechanism of AUD development (i.e., LR to alcohol). Through the combination of multiple genetically-informed datasets, the current study is well-positioned to examine the genetic factors underlying a well-defined endophenotype of AUD, LR to alcohol. Additionally, polygenic prediction models will serve to expand our knowledge of the polygenic architecture underlying LR to alcohol, as well as the shared genetic contributions between LR to alcohol and AUD. By gaining a more precise understanding of the genetic architecture of LR, and the subsequent susceptibility for AUD, we can make substantial progress towards integrating this genetic information in treatment approaches with the goal of developing personalized AUD intervention efforts. Training Aims The current proposal will allow the applicant to gain valuable experience in management, integration, and data analysis procedures for investigating alcohol use outcomes in large-scale, genetically-informed datasets, as well as knowledge in the application of state-of-the-art polygenic modeling approaches for examining the aggregate effect of genetic variation across the genome. The nature of these training experiences will provide an immersive experience for the applicant through close collaboration with multiple research groups. Thus, successful completion of these training aims will provide the foundation for the applicant’s career objective of obtaining a tenure-track academic position investigating AUD phenotypes in large, consortia-derived, genetic datasets and how best to leverage findings from such studies to improve clinical outcomes.

(7)项目摘要/摘要 具体目标 目前的提议首先旨在通过以下方式扩大先前对酒精反应水平(LR)的遗传研究 进行迄今为止规模最大的全基因组关联研究(GWAS)，通过对 多个样本具有现有的SRE(酒精影响的自我评级)和GWAS数据。第二个目标是 使用来自LR所描述的GWAS的汇总数据在独立样本中创建多基因风险分数 为了确定酒精对LR的遗传影响是否以及在多大程度上作为一种 澳元的风险因素。 方法 为了达到上述目标，数据集将按照标准质量控制(Qc)进行处理。 程序(例如，Anderson等人，2010年)，允许将基因归因于共同的参考小组以及 使用适用于个别研究设计的方法对每个数据集进行GWA分析。对于所有已识别的 样本(见所附投稿信函)Marc Schuckit博士(顾问)将在以下方面提供关键支持 关于使用SRE表型的决定。所有数据分析程序都将在 与Ian Gizer博士(赞助者)、Arpana Agrawal博士(顾问)和各自的数据集进行协调 确保所有数据都按照双方商定的程序进行分析。跟随 将执行个人研究水平的GWA分析、标准化的GWA元分析QC程序 (Winkler等人，2014)，结合所有样本的结果的荟萃分析将使用 金属中的固定效果模型(Willer等人，2010年)。最后，来自SRE荟萃分析的结果将被用于 计算独立目标样本中的多基因风险分数(PR)，以检查 对于AUD结果，LR到酒精PRs。澳大利亚双胞胎家庭(OZ-ALC GWAS)样本获取自 将使用基因型和表型数据库(DBGaP)来实现这第二个目标。 长期目标 当前提案的总体目标是利用GWA荟萃分析程序和多基因 综合多个GWA数据集的定量数据的建模方法，以提高我们的 了解AUD病因学的遗传结构，以及公认的生物学风险 AUD发生的机制(即，对酒精的LR)。通过多种基因信息的组合 数据集，目前的研究很好地检查了潜在的明确的遗传因素 AUD、LR对酒精的内表型。此外，多基因预测模型将用于扩展我们的 关于酒精引起的LR的多基因结构的知识，以及共同的遗传贡献 在酒精和澳元之间。通过更准确地了解LR的遗传结构， 以及随之而来的澳门氏症易感性，我们可以在整合这种基因方面取得实质性进展 治疗方法方面的信息，目标是开发个性化的AUD干预努力。 培训目标 目前的提案将允许申请人在管理、集成和数据方面获得宝贵的经验 在大规模遗传信息数据集中调查酒精使用结果的分析程序，如 以及应用最先进的多基因建模方法来检查 整个基因组的遗传变异的综合效应。这些培训经验的性质将提供 通过与多个研究小组的密切合作，为申请者提供身临其境的体验。因此， 成功完成这些培训目标将为申请者的职业目标奠定基础 获得终身教职，研究大型、财团衍生的、遗传的AUD表型 数据集，以及如何最好地利用这些研究的结果来改善临床结果。